class_docstr: A ``MetadataField`` is a ``Field`` that does not get converted into tensors.  It just carries
  side information that might be needed later on, for computing some third-party metric, or
  outputting debugging information, or whatever else you need.  We use this in the BiDAF model,
  for instance, to keep track of question IDs and passage token offsets, so we can more easily
  use the official evaluation script to compute metrics.
  
  We don't try to do any kind of smart combination of this field for batched input - when you use
  this ``Field`` in a model, you'll get a list of metadata objects, one for each instance in the
  batch.
  
  Parameters
  ----------
  metadata : ``Any``
      Some object containing the metadata that you want to store.  It's likely that you'll want
      this to be a dictionary, but it could be anything you want.
code: def batch_tensors(cls, tensor_list):  # type: ignore
      return tensor_list
  
file_path: magnitude/pymagnitude/third_party/allennlp/data/fields/metadata_field.py
imports: from __future__ import absolute_import
  from allennlp.data.fields.field import Field
label_desc: Use image node_id 5 for calling the MetadataField obj's underlying member method code with example usage: obj.batch_tensors(cls, tensor_list) and returns: tensor_list